# HG changeset patch # User gregory-minevich # Date 1399669181 14400 # Node ID 918964ff9be5d579cc68b73d5b2b4dbe4b3fc09d # Parent f19399eea0c476268cc44232c68ed171f3864c93 Uploaded diff -r f19399eea0c4 -r 918964ff9be5 SNP_Mapping.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/SNP_Mapping.py Fri May 09 16:59:41 2014 -0400 @@ -0,0 +1,458 @@ +#!/usr/bin/python + +import re +import sys +import optparse +import csv +import re +import pprint +from decimal import * +from rpy import * + +def main(): + csv.field_size_limit(1000000000) + + parser = optparse.OptionParser() + parser.add_option('-v', '--sample_vcf', dest = 'sample_vcf', action = 'store', type = 'string', default = None, help = "Sample VCF from GATK Unified Genotyper") + parser.add_option('-l', '--loess_span', dest = 'loess_span', action = 'store', type = 'float', default = .1, help = "Loess span") + parser.add_option('-d', '--d_yaxis', dest = 'd_yaxis', action = 'store', type = 'float', default = 1, help = "y-axis upper limit for dot plot") + parser.add_option('-y', '--h_yaxis', dest = 'h_yaxis', action = 'store', type = 'int', default = 0, help = "y-axis upper limit for histogram plot") + parser.add_option('-c', '--points_color', dest = 'points_color', action = 'store', type = 'string', default = "gray27", help = "Color for data points") + parser.add_option('-k', '--loess_color', dest = 'loess_color', action = 'store', type = 'string', default = "red", help = "Color for loess regression line") + parser.add_option('-z', '--standardize', dest = 'standardize', default= 'true', help = "Standardize X-axis") + parser.add_option('-b', '--break_file', dest = 'break_file', action = 'store', type = 'string', default = 'C.elegans', help = "File defining the breaks per chromosome") + parser.add_option('-x', '--bin_size', dest = 'bin_size', action = 'store', type = 'int', default = 1000000, help = "Size of histogram bins, default is 1mb") + parser.add_option('-n', '--normalize_bins', dest = 'normalize_bins', default= 'true', help = "Normalize histograms") + + + parser.add_option('-o', '--output', dest = 'output', action = 'store', type = 'string', default = None, help = "Output file name") + parser.add_option('-s', '--location_plot_output', dest = 'location_plot_output', action = 'store', type = 'string', default = "SNP_Mapping_Plot.pdf", help = "Output file name of SNP plots by chromosomal location") + + (options, args) = parser.parse_args() + + vcf_info = parse_vcf(sample_vcf = options.sample_vcf) + + output_vcf_info(output = options.output, vcf_info = vcf_info) + + rounded_bin_size = int(round((float(options.bin_size) / 1000000), 1) * 1000000) + + normalized_histogram_bins_per_mb = calculate_normalized_histogram_bins_per_xbase(vcf_info = vcf_info, xbase = rounded_bin_size, normalize_bins = options.normalize_bins) + max_y_hist_mb = normalized_histogram_bins_per_mb[max(normalized_histogram_bins_per_mb, key = lambda x: normalized_histogram_bins_per_mb.get(x) )] + + normalized_histogram_bins_per_5kb = calculate_normalized_histogram_bins_per_xbase(vcf_info = vcf_info, xbase = (rounded_bin_size / 2), normalize_bins = options.normalize_bins) + max_y_hist_5kb = normalized_histogram_bins_per_5kb[max(normalized_histogram_bins_per_5kb, key = lambda x: normalized_histogram_bins_per_5kb.get(x) )] + + max_y_hist_overall = myround(max(max_y_hist_mb, max_y_hist_5kb) + int(round(round(max(max_y_hist_mb, max_y_hist_5kb)) * .1))) + + break_dict = parse_breaks(break_file = options.break_file) + + output_scatter_plots_by_location(location_plot_output = options.location_plot_output, vcf_info = vcf_info, loess_span=options.loess_span, d_yaxis=options.d_yaxis, h_yaxis=options.h_yaxis, points_color=options.points_color, loess_color=options.loess_color, standardize =options.standardize, normalized_hist_per_mb = normalized_histogram_bins_per_mb, normalized_hist_per_5kb = normalized_histogram_bins_per_5kb, breaks = break_dict, rounded_bin_size = rounded_bin_size, max_y_hist_overall = max_y_hist_overall) + + +def myround(x, base=10): + return int(base * round(float(x)/base)) + +def skip_headers(reader = None, i_file = None): + # count headers + comment = 0 + while reader.next()[0].startswith('#'): + comment = comment + 1 + + # skip headers + i_file.seek(0) + for i in range(0, comment): + reader.next() + +def parse_breaks(break_file = None): + if break_file == 'C.elegans': + break_dict = { 'I' : 16 , 'II' : 16, 'III' : 14, 'IV' : 18, 'V' : 21, 'X' : 18 } + return break_dict + elif break_file == 'Brachypodium': + break_dict = { '1' : 75 , '2' : 60, '3' : 60, '4' : 50, '5' : 30 } + return break_dict + elif break_file == 'Arabidopsis': + break_dict = { '1' : 31 , '2' : 20, '3' : 24, '4' : 19, '5' : 27 } + return break_dict + else: + i_file = open(break_file, 'rU') + break_dict = {} + reader = csv.reader(i_file, delimiter = '\t') + for row in reader: + chromosome = row[0].upper() + chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE) + chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE) + break_count = row[1] + break_dict[chromosome] = int(break_count) + return break_dict + + +def location_comparer(location_1, location_2): + chr_loc_1 = location_1.split(':')[0] + pos_loc_1 = int(location_1.split(':')[1]) + + chr_loc_2 = location_2.split(':')[0] + pos_loc_2 = int(location_2.split(':')[1]) + + if chr_loc_1 == chr_loc_2: + if pos_loc_1 < pos_loc_2: + return -1 + elif pos_loc_1 == pos_loc_1: + return 0 + elif pos_loc_1 > pos_loc_2: + return 1 + elif chr_loc_1 < chr_loc_2: + return -1 + elif chr_loc_1 > chr_loc_2: + return 1 + +def output_vcf_info(output = None, vcf_info = None): + o_file = open(output, 'wb') + writer = csv.writer(o_file, delimiter = '\t') + + writer.writerow(["#Chr\t", "Pos\t", "Alt Count\t", "Ref Count\t", "Read Depth\t", "Ratio\t"]) + + location_sorted_vcf_info_keys = sorted(vcf_info.keys(), cmp=location_comparer) + + for location in location_sorted_vcf_info_keys: + alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location] + + location_info = location.split(':') + chromosome = location_info[0] + position = location_info[1] + + writer.writerow([chromosome, position, alt_allele_count, ref_allele_count, read_depth, ratio]) + + o_file.close() + +def output_scatter_plots_by_location(location_plot_output = None, vcf_info = None, loess_span="", d_yaxis="", h_yaxis="", points_color="", loess_color="", standardize=None, normalized_hist_per_mb = None, normalized_hist_per_5kb = None, breaks = None, rounded_bin_size = 1000000, max_y_hist_overall = ""): + positions = {} + current_chr = "" + prev_chr = "" + + x_label = "Location (Mb)" + filtered_label = '' + + location_sorted_vcf_info_keys = sorted(vcf_info.keys(), cmp=location_comparer) + + break_unit = Decimal(rounded_bin_size) / Decimal(1000000) + max_breaks = max(breaks.values()) + + try: + r.pdf(location_plot_output, 8, 8) + + for location in location_sorted_vcf_info_keys: + current_chr = location.split(':')[0] + position = location.split(':')[1] + + alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location] + + if prev_chr != current_chr: + if prev_chr != "": + hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = prev_chr) + hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = prev_chr) + + if h_yaxis == 0: + plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = prev_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=max_y_hist_overall, points_color=points_color, loess_color=loess_color, breaks = breaks[prev_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit) + else: + plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = prev_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=h_yaxis, points_color=points_color, loess_color=loess_color, breaks = breaks[prev_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit) + + prev_chr = current_chr + positions = {} + + positions[position] = ratio + + hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = current_chr) + hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = current_chr) + + if h_yaxis == 0: + plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = current_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=max_y_hist_overall, points_color=points_color, loess_color=loess_color, breaks = breaks[current_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit) + else: + plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = current_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=h_yaxis, points_color=points_color, loess_color=loess_color, breaks = breaks[current_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit) + + r.dev_off() + + except Exception as inst: + print inst + print "There was an error creating the location plot pdf... Please try again" + +def get_hist_dict_by_chr(normalized_hist_per_xbase = None, chr = ''): + hist_dict = {} + + for location in normalized_hist_per_xbase: + chromosome = location.split(':')[0] + if chromosome == chr: + position = int(location.split(':')[1]) + hist_dict[position] = normalized_hist_per_xbase[location] + + max_location = max(hist_dict.keys(), key=int) + for i in range(1, max_location): + if i not in hist_dict: + hist_dict[i] = 0 + + return hist_dict + + +def plot_data(chr_dict = None, hist_dict_mb = None, hist_dict_5kb = None, chr = "", x_label = "", divide_position = False, draw_secondary_grid_lines = False, loess_span=None, d_yaxis=None, h_yaxis=None, points_color="", loess_color="", breaks = None, standardize= None, max_breaks = 1, break_unit = 1): + ratios = "c(" + positions = "c(" + + for position in chr_dict: + ratio = chr_dict[position] + if divide_position: + position = float(position) / 1000000.0 + positions = positions + str(position) + ", " + ratios = ratios + str(ratio) + ", " + + if len(ratios) == 2: + ratios = ratios + ")" + else: + ratios = ratios[0:len(ratios) - 2] + ")" + + if len(positions) == 2: + positions = positions + ")" + else: + positions = positions[0:len(positions) - 2] + ")" + + r("x <- " + positions) + r("y <- " + ratios) + + hist_mb_values = "c(" + for position in sorted(hist_dict_mb): + hist_mb_values = hist_mb_values + str(hist_dict_mb[position]) + ", " + + if len(hist_mb_values) == 2: + hist_mb_values = hist_mb_values + ")" + else: + hist_mb_values = hist_mb_values[0:len(hist_mb_values) - 2] + ")" + + hist_5kb_values = "c(" + for position in sorted(hist_dict_5kb): + hist_5kb_values = hist_5kb_values + str(hist_dict_5kb[position]) + ", " + + if len(hist_5kb_values) == 2: + hist_5kb_values = hist_5kb_values + ")" + else: + hist_5kb_values = hist_5kb_values[0:len(hist_5kb_values) - 2] + ")" + + r("xz <- " + hist_mb_values) + r("yz <- " + hist_5kb_values) + + + max_break_str = str(max_breaks) + break_unit_str = str(Decimal(break_unit)) + half_break_unit_str = str(Decimal(break_unit) / Decimal(2)) + break_penta_unit_str = str(Decimal(break_unit) * Decimal(5)) + + if (standardize=='true'): + r("plot(x, y, ,cex=0.60, xlim=c(0," + max_break_str + "), main='LG " + chr + " (Hawaiian Variant Mapping)', xlab= '" + x_label + "', ylim = c(0, %f " %d_yaxis + "), ylab='Ratios of mapping strain alleles/total reads (at SNP positions)', pch=10, col='"+ points_color +"')") + r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')") + r("axis(1, at=seq(0, " + max_break_str + ", by=" + break_unit_str + "), labels=FALSE, tcl=-0.5)") + r("axis(1, at=seq(0, " + max_break_str + ", by=" + half_break_unit_str + "), labels=FALSE, tcl=-0.25)") + r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)") + elif (standardize=='false'): + r("plot(x, y, cex=0.60, main='LG " + chr + " (Hawaiian Variant Mapping)', xlab= '" + x_label + "', ylim = c(0, %f " %d_yaxis + "), ylab='Ratios of mapping strain alleles/total reads (at SNP positions)', pch=10, col='"+ points_color +"')") + r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')") + r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)") + r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)") + r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)") + + if draw_secondary_grid_lines: + r("abline(h = seq(floor(min(y)), 1, by=0.1), v = seq(floor(min(x)), length(x), by= 1), col='gray')") + else: + r("grid(lty = 1, col = 'gray')") + + if (standardize=='true'): + r("barplot(xz, xlim=c(0, " + max_break_str + "), ylim = c(0, " + str(h_yaxis) + "), yaxp=c(0, " + str(h_yaxis) + ", 1), space = 0, col='darkgray', width = " + break_unit_str + ", xlab='Location (Mb)', ylab='Normalized frequency of pure parental alleles ', main='LG " + chr + " (Hawaiian Variant Mapping)')") + r("barplot(yz, space = 0, add=TRUE, width = " + half_break_unit_str + ", col=rgb(1, 0, 0, 1))") + r("axis(1, hadj = 1, at=seq(0, " + max_break_str + ", by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)") + r("axis(1, at=seq(0, " + max_break_str + ", by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)") + r("axis(1, at=seq(0, " + max_break_str + ", by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)") + elif (standardize=='false'): + r("barplot(xz, ylim = c(0, " + str(h_yaxis) + "), yaxp=c(0, " + str(h_yaxis) + ", 1), space = 0, col='darkgray', width = 1, xlab='Location (Mb)', ylab='Normalized frequency of pure parental alleles ', main='LG " + chr + " (Hawaiian Variant Mapping)')") + r("barplot(yz, space = 0, add=TRUE, width = 0.5, col=rgb(1, 0, 0, 1))") + r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)") + r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)") + r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)") + + + +def calculate_normalized_histogram_bins_per_xbase(vcf_info = None, xbase = 1000000, normalize_bins = None): + normalized_histogram_bins_per_xbase = {} + + ref_snp_count_per_xbase = get_ref_snp_count_per_xbase(vcf_info = vcf_info, xbase = xbase) + + mean_zero_snp_count_per_chromosome = get_mean_zero_snp_count_per_chromosome(vcf_info = vcf_info, xbase = xbase) + + zero_snp_count_per_xbase = get_zero_snp_count_per_xbase(vcf_info = vcf_info, xbase = xbase) + + + for location in ref_snp_count_per_xbase: + chromosome = location.split(':')[0] + mean_zero_snp_count = mean_zero_snp_count_per_chromosome[chromosome] + ref_snp_count = ref_snp_count_per_xbase[location] + + zero_snp_count = 0 + if location in zero_snp_count_per_xbase: + zero_snp_count = zero_snp_count_per_xbase[location] + + if normalize_bins == 'true': + if zero_snp_count == 0 or ref_snp_count == 0: + normalized_histogram_bins_per_xbase[location] = 0 + elif zero_snp_count == ref_snp_count: + normalized_histogram_bins_per_xbase[location] = 0 + else: + normalized_histogram_bins_per_xbase[location] = (Decimal(zero_snp_count) / (Decimal(ref_snp_count)-Decimal(zero_snp_count))) * Decimal(mean_zero_snp_count) + else: + normalized_histogram_bins_per_xbase[location] = zero_snp_count + + return normalized_histogram_bins_per_xbase + + +def get_ref_snp_count_per_xbase(vcf_info = None, xbase = 1000000): + ref_snps_per_xbase = {} + + for location in vcf_info: + location_info = location.split(':') + + chromosome = location_info[0].upper() + chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE) + chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE) + + position = location_info[1] + xbase_position = (int(position) / xbase) + 1 + + location = chromosome + ":" + str(xbase_position) + if location in ref_snps_per_xbase: + ref_snps_per_xbase[location] = ref_snps_per_xbase[location] + 1 + else: + ref_snps_per_xbase[location] = 1 + + return ref_snps_per_xbase + + + +def get_mean_zero_snp_count_per_chromosome(vcf_info, xbase = 1000000): + sample_snp_count_per_xbase = {} + + for location in vcf_info: + alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location] + + location_info = location.split(':') + chromosome = location_info[0] + position = location_info[1] + xbase_position = (int(position) / xbase) + 1 + xbase_location = chromosome + ":" + str(xbase_position) + + if int(alt_allele_count) == 0: + if xbase_location in sample_snp_count_per_xbase: + sample_snp_count_per_xbase[xbase_location] = sample_snp_count_per_xbase[xbase_location] + 1 + else: + sample_snp_count_per_xbase[xbase_location] = 1 + + elif int(alt_allele_count) != 0 and xbase_location not in sample_snp_count_per_xbase: + sample_snp_count_per_xbase[xbase_location] = 0 + + mean_zero_snp_count_per_chromosome = {} + for location in sample_snp_count_per_xbase: + chromosome = location.split(':')[0] + sample_count = sample_snp_count_per_xbase[location] + if chromosome in mean_zero_snp_count_per_chromosome: + mean_zero_snp_count_per_chromosome[chromosome].append(sample_count) + else: + mean_zero_snp_count_per_chromosome[chromosome] = [sample_count] + + for chromosome in mean_zero_snp_count_per_chromosome: + summa = sum(mean_zero_snp_count_per_chromosome[chromosome]) + count = len(mean_zero_snp_count_per_chromosome[chromosome]) + + mean_zero_snp_count_per_chromosome[chromosome] = Decimal(summa) / Decimal(count) + + return mean_zero_snp_count_per_chromosome + + +def get_zero_snp_count_per_xbase(vcf_info = None, xbase = 1000000): + zero_snp_count_per_xbase = {} + + for location in vcf_info: + alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location] + + location_info = location.split(':') + chromosome = location_info[0] + position = location_info[1] + xbase_position = (int(position) / xbase) + 1 + xbase_location = chromosome + ":" + str(xbase_position) + + if int(alt_allele_count) == 0: + if xbase_location in zero_snp_count_per_xbase: + zero_snp_count_per_xbase[xbase_location] = zero_snp_count_per_xbase[xbase_location] + 1 + else: + zero_snp_count_per_xbase[xbase_location] = 1 + + elif int(alt_allele_count) != 0 and xbase_location not in zero_snp_count_per_xbase: + zero_snp_count_per_xbase[xbase_location] = 0 + + return zero_snp_count_per_xbase + + +def parse_vcf(sample_vcf = None): + i_file = open(sample_vcf, 'rU') + reader = csv.reader(i_file, delimiter = '\t', quoting = csv.QUOTE_NONE) + + skip_headers(reader = reader, i_file = i_file) + vcf_info = {} + + for row in reader: + chromosome = row[0].upper() + chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE) + chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE) + + + if chromosome != 'MTDNA': + position = row[1] + #ref_allele = row[2] + #read_depth = row[3] + #read_bases = row[4] + + vcf_format_info = row[8].split(":") + vcf_allele_freq_data = row[9] + + read_depth_data_index = vcf_format_info.index("DP") + read_depth = vcf_allele_freq_data.split(":")[read_depth_data_index] + + ref_and_alt_counts_data_index = vcf_format_info.index("AD") + ref_and_alt_counts = vcf_allele_freq_data.split(":")[ref_and_alt_counts_data_index] + ref_allele_count = ref_and_alt_counts.split(",")[0] + alt_allele_count = ref_and_alt_counts.split(",")[1] + + location = chromosome + ":" + position + + if (Decimal(read_depth)!=0): + getcontext().prec = 6 + ratio = Decimal(alt_allele_count) / Decimal(read_depth) + + vcf_info[location] = (alt_allele_count, ref_allele_count, read_depth, ratio) + + #debug line + #print chromosome, position, read_depth, ref_allele_count, alt_allele_count, ratio, id + + i_file.close() + + return vcf_info + +def parse_read_bases(read_bases = None, alt_allele = None): + read_bases = re.sub('\$', '', read_bases) + read_bases = re.sub('\^[^\s]', '', read_bases) + + ref_allele_matches = re.findall("\.|\,", read_bases) + ref_allele_count = len(ref_allele_matches) + + alt_allele_matches = re.findall(alt_allele, read_bases, flags = re.IGNORECASE) + alt_allele_count = len(alt_allele_matches) + + #debug line + #print read_bases, alt_allele, alt_allele_count, ref_allele_count + + return ref_allele_count, alt_allele_count + +if __name__ == "__main__": + main()